China Smart Road Industry Report 2020: Intelligent Roadside Perception Analysis - With Greater Policy Support, the RMB10 Billion Intelligent Roadside Perception Market Takes Off - ResearchAndMarkets.com
DUBLIN--(BUSINESS WIRE)--Sep 28, 2020--
The “Smart Road: Intelligent Roadside Perception Industry Report, 2020” report has been added to ResearchAndMarkets.com’s offering.
With Greater Policy Support, the RMB10 Billion Intelligent Roadside Perception Market Takes Off
In this Smart Road: Intelligent Roadside Perception Industry Report, 2020, we analyze policies, industry chain and technologies, market size, business model and suppliers in the intelligent roadside perception industry (including RSU, roadside sensor, MEC and cloud control platform).
With the advancement of cooperative vehicle infrastructure system, China and the industry have come to know that the priority should be given to coordinated development between infrastructure and vehicle more than just vehicle. A plurality of policies was issued for intelligent road construction in China in 2020 alone.
Wherein, the Guiding Opinions on Promoting the Construction of New Infrastructures for Transportation released in August 2020 makes it clear that ubiquitous perception facilities should be pervasive enough in the transportation industry; the Guide for Layout of Internet of Vehicles (IoV) Roadside Facilities, an association standard concerning roadside facilities published in August 2020, specifies layout of IoV roadside facilities in the C-V2X-based IoV traffic circumstance, and further promotion of roadside and cloud equipment to be unified.
With policy support, China’s intelligent roadside perception market (including radar, camera, etc.) is proliferating fast and is expected to be worth RMB40 billion by 2025. In the market, LiDAR costs the most in deployment, with a single set even priced up to tens of thousands of yuan. Yet LiDAR performs much better in roadside scenarios, notably complex intersections, for it could recognize target attributes precisely and offer far more accurate, reliable data combining with cameras. LiDAR is still at the start of application in roadside end and has yet to be used massively. If deployed on a large scale, the price of LiDAR will take a nosedive.
IT giants race to enter
Evolvement of cooperative vehicle infrastructure system (CVIS) is decided by use of roadside equipment. Amid the rising penetration of intelligent roadside perception systems, the intelligent transportation network will be built up to further improve operational efficiency of cities and roads with technologies from edge computing to cloud control. Intelligent roadside perception system is a foundation for development of intelligent transportation.
Additionally, widespread layout of intelligent roadside equipment will drag down installation cost of vehicle V2X devices and push up their penetration. Only sound development of CVIS may make L4/L5 automated driving a reality.
IT tycoons like Huawei and BAT (Baidu, Alibaba and Tencent) who are bullish about the prospect of intelligent roadside equipment, scramble to march into the market.
Baidu focuses on research and development of roadside perception capabilities that meet needs of autonomous driving scenarios and fuse with V2X roadside perception information offered by the vehicle autonomous driving system. In the first half of 2020, Baidu has won the biddings for intelligent transportation projects in Nanjing, Hefei, Yangquan, Chongqing, to name a few.
Alibaba remains superior in infrastructure end, with Cainiao Alliance and ET City Brain. The giant will develop vehicle-infrastructure cooperation using technologies such as Alibaba Cloud Control Platform, AliOS and intelligent roadside facilities.
Tencent has a plan to expedite edge computing equipment installations and to build an open source platform for edge computing together with several partners.
Huawei makes concurrent efforts on vehicle and infrastructure ends, having rolled out products like roadside unit, EI-based Traffic Intelligent Twins, and OceanConnect intelligent transportation platform.
Key Topics Covered:
1 National Guiding Policies and Path Planning
1.1 Intelligent Roadside Perception Policy
1.1.1 National Strategic Guiding Policies for Intelligent Highway
1.1.2 Level of Intelligent Technology for Intelligent Highway
1.1.3 Correspondence of Level between Intelligent Highway Technology and Autonomous Driving
1.1.4 Evaluation Contents and Standards of Intelligent Highway Pilot Projects
1.1.5 Standards for Intelligent Highway Infrastructure Projects Get Improved Gradually
1.1.6 Building of Intelligent Roadside Standard System
1.2 Development Plan for Intelligent Roadside Perception
1.2.1 Vehicle-infrastructure Cooperation Promotes Intelligent Transportation
1.2.2 Development Plan for Intelligent Highway
1.2.3 Construction of 5G Intelligent Highway
1.2.4 Requirements on Deployment of Intelligent Roadside Facilities in Intelligent Highway Pilot Projects
1.2.5 Path Planning of Industrialization of Intelligent Roadside Perception under the Internet of Vehicles (IOV) Framework (2019-2025)
2 Key Technologies and Industry Chain of Roadside Perception
2.1 Key Roadside Perception Technology
2.1.1 Role of Intelligent Roadside Perception Equipment
2.1.2 Intelligent Roadside Perception Solution
2.1.3 Intelligent Roadside Perception System
2.1.4 Perception Technology
2.1.5 Transmission Technology
2.1.6 Control Technology
2.1.7 Computing Technology
2.1.8 System Integration Technology
2.1.9 Technology of Dynamic Analysis and Security Decision
2.1.10 Key Technology for Roadside Perception-Multi-sensor Fusion
2.1.11 Technological Challenges to Roadside Perception
2.1.12 Roadside Perception Technological Solutions of Major Suppliers
2.1.13 Roadside Perception Product Layout of Major Suppliers
2.2 Intelligent Roadside Perception Industry Chain
2.2.1 New Intelligent Transportation System with Vehicle-Infrastructure-Cloud Collaboration
2.2.2 Role of Vehicle-Infrastructure Cooperation in Intelligent Transportation
2.2.3 Basic Application Scenarios of Intelligent Roadside Perception
2.2.4 Intelligent Roadside Perception Industry Chain
2.2.5 Industrial Ecosystem of CVIS-based Roadside Perception
2.2.6 Roles that All Parties on the Industry Chain Play in the CVIS-based Intelligent Transportation System
2.2.7 Obstacles to Industrialization of C-V2X Roadside Facilities in China
3 Roadside Perception Market Size and Trend
3.1 Intelligent Roadside Perception Market Size
3.1.1 Market Size - Estimated Data and Assumption
3.1.2 Market Size Estimation - Intelligent Roadside Perception Equipment (RSU + Perception)
3.1.3 Market Size Estimation - Cloud Control Platform
3.1.4 Market Size Estimation - Summary (RSU + Cloud Platform + MEC)
3.1.5 Trend of Market Size
3.1.6 Development Trend of Intelligent Roadside Perception
3.2 Patents of Intelligent Roadside Perception Equipment
3.2.1 RSU Patents
3.2.2 MEC Patents
4 Roadside Perception Business Models and Cases
4.1 Roadside Perception Business Models
4.1.2 Prerequisites for Mature Business Models
4.1.3 How to Choose Application Scenarios in Early Industrialization
4.1.4 The Best Application Scenarios in the Early Stage
4.1.5 Exploration of Scenario-based Application Models
4.1.6 IOV Business Model
4.1.7 Challenges to IOV Business Model
4.1.8 Roadside Perception Equipment Investment and Business Model
4.1.9 Commercial Deployments in Intelligent Roadside Equipment
4.1.10 Exploration of Business Model for Intelligent Roadside Equipment
4.1.11 MEC Commercial Deployment Strategy
4.1.12 Deployment of MEC in IOV Scenarios
4.1.13 MEC Business Model
4.1.14 Scenario-based Application Case 1: Platooning on Highway
4.1.15 Scenario-based Application Case 2: Connected Autonomous Driving for Smart Mines
4.1.16 Scenario-based Application Case 2: Connected Autonomous Driving for Smart Mines (Analysis)
4.2 Intelligent Roadside Perception Application Cases
4.2.1 Intelligent Highway
4.2.2 Urban Area
4.2.3 Enclosed or Semi-enclosed Area
4.2.4 Intelligent Pole
4.2.5 Intelligent Pole Architecture
5 Roadside Perception System Solution Providers
- Vanjee Technology
- China TransInfo Technology
- NEBULA LINK
- Changsha Intelligent Driving Institute (CiDi)
- Cohda Wireless
- China Automotive Engineering Research Institute
- LeiShen Intelligent System
- China Unicom
For more information about this report visit https://www.researchandmarkets.com/r/mdqv2h
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SOURCE: Research and Markets
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PUB: 09/28/2020 12:38 PM/DISC: 09/28/2020 12:38 PM